Bicycle Improvement: Flexible Electric Motor System Mohamed, Aezeden; Oyekola, Peter Oluwatosin; Pumwa, John
International journal of recent technology and engineering,
09/2019, Letnik:
8, Številka:
3
Journal Article
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This paper is an educational design course project on the modification of a bicycle frame and engineering components to enhance mobility and reduce effort while cyclic. The project was simulated with ...computer aided software which includes material selection and structural modification, which is an important element of design. The brushless DC motor is assembled over the back wheel as propellant. The correlative material/application processes and materials selection are briefly discussed in this study.
Selecting the right cutting tool material for the type of workpiece material plays a very important role in the machining process. The efficiency of the machining process is greatly influenced by ...this selection. The tables in the manuals or the manufacturer's instructions are commonly used documents for the selection of cutting tool materials. Within each of these document types, the cutting tool materials were described by different criteria. So, tool selection is considered as a multi-criteria decision-making activity. The values of the criteria for each type of cutting tool can be a number or a certain range. This study proposes a new method to rank and select cutting tools. First, a ranking of the solutions for each criterion will be performed. This ranking is based on the mean value of the criteria in each solution. Therefore, this method is called "Ranking the Solutions based on the Mean Value of Criteria - RSMVC". The RSMVC method was proven to be a highly reliable method for ranking the cutting tool materials. These results were successfully verified when solving the problems in different cases of cutter material selection.
This paper discusses crucial aspects related to crucibles and coatings in the scope of silicon crystallization and melting. The paper thoroughly examines different types of crucibles, highlighting ...both their principal challenges and advantages. Additionally, it investigates coatings in-depth, examining their roles, stability, and wetting behaviour. Crucible selection criteria, including thermal properties, melt contamination, cost, reusability, and design considerations, are also addressed. Furthermore, the paper discusses the thermodynamics of the Si-C-N-O system in the context of silicon operations at high temperatures. This review provides valuable insights for researchers and specialists in the field of silicon production and crystallization, aiding in the selection and utilization of crucibles and coatings for improved process performance.
Astonishingly 3D printing has excited the world of aerospace. This paper takes stock of the popular 3D printing processes in aerospace. Reasons for their popularity over the traditional manufacturing ...processes are dwelled upon. Materials developed specially for aerospace applications along with their characteristics are discussed. Ongoing activities related to 3D printing at various companies and organisations around the world are looked into. Project works in the area of extra-terrestrial printing are also highlighted. Even though 3D printing processes are operationally simple, they do have limitations in terms of the type, quality, and quantity of the materials they can handle. This paper underlines these points while discussing drawbacks of the printed components. Challenges associated with 3D printing in microgravity are also touched upon. Finally, a glimpse is taken into the future appearance of aerospace industry with 3D printing.
Since traditional Multi-Criteria Decision Making (MCDM) approaches have become defunct, academics have shifted their attention to developing hybrid MCDM models, which use a combination of two or more ...MCDM methods to solve decision-making issues. Using Additive Ratio Assessment (ARAS), the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), and Gray Relational Analysis (GRA), the authors of this work aimed to develop unique hybrid MCDM systems. To show how well this hybrid model works, it is applied to a real-world material selection scenario including seven possible materials and seven criteria. Results from this hybrid model are compared to those from other standalone MCDM tools as well as previously published findings based on the same illustrative situation. 3rd Material is the best option, while the 2nd material is the worst option, among these seven choices which are consistent enough to imply such a conclusion. Using many MCDM strategies is recommended since no one strategy can ensure making the best decision. Because of this, the Copeland approach is used to combine the rankings from the 11 methodologies and get a consensus result. The results from the Copeland technique show that the final consensus rank of materials may be different from the rank of the hybrid model and other standalone MCDM tools. As a result, it is crucial to use a multi-pronged approach. Furthermore, the Spearman Correlation Coefficient (SCC) shows that the suggested rankings produced from the different approaches have a significant ranking association with one another.
Material selection is a topic of pivotal importance in the optimal design and development of industrial products. Increasing demand for high-performance materials with desirable and tailor-made ...properties is expected to drive the future market. This paper examines the application of multicriteria decision-making techniques like AHP, TOPSIS, EDAS, VIKOR, and Taguchi-based super ranking concepts for the selection of optimal aluminum alloy material for the sheet metal forming process. The criteria used to evaluate the optimal material selection were identified as yield strength, tensile strength, thermal conductivity, impact, density, specific heat, coefficient of thermal expansion, and % elongation. The most ranked aluminum material frequency is selected for sheet metal forming simulation using DEFORM, a process simulation FEM-based tool. An integrated Taguchi DOE and process simulation were carried out for the best-ranked AA2024 aluminum material. The results showed that the MCDM and Taguchi-based super ranking concept provides an intelligent and methodical assessment for solving material selection from a finite set of alternatives for the sheet metal forming process. The group decision behavior, agility, and flexibility in including multiple decision-making criteria for overall comparative analysis of materials, and manufacturing processes with uncertainty make MCDM methods a definitive tool for materials and manufacturing process selection.
► Multi-Criterion Decision Making coupled with environmental impact analysis. ► Evaluation of material selection process in fuzzy environment. ► Minimisation of environmental impact during material ...selection process. ► Application to an instrument panel used in electric car.
Material selection is a complex process, since the process includes many criteria, determination of criteria weight and the most important factor is that the selection of appropriate criterion. The last factor indicates that the criterion must be selected in a manner, such that the selection based upon the known material parameters and the requirements of the application. Therefore the material selection can be done using MCDM (Multi Criterion Decision Making) methods. Since the inputs provided by the decision maker in linguistic manner, there is a possible chance of getting incomplete problems. So in order to overcome the problem, the inputs could be provided as fuzzy numbers. Since fuzzy set represents the uncertainty in human perceptions. In this paper, VIKOR (VlseKriterijumska Optimizacija I Kompromisno Resenje in Serbian, means Multicriteria Optimisation and Compromise Solution) has been used a MCDM tool for the selection of alternate material for instrument panel used in electric car and in order to evaluate this selection process in fuzzy environment, fuzzy based VIKOR is used. In addition to the fuzzy VIKOR method, the environmental impacts are also considered and compared for the four materials. The results achieved in both the assessment, showed that Polypropylene could be an alternate material for the instrument panel. The objective of this study is to develop a rational method to select the best material for an application based upon known material parameters and the requirements of the application.
This article aims to present our experience with transmedia storytelling in the design of materials selection, integrating two disciplines within an undergraduate mechanical engineering curriculum in ...Brazil. The students' project involved developing a narrative within the fictional universe of superheroes while exploring material properties using Ashby's methodology. The study aimed at answering two key questions: (1) Can transmedia storytelling contribute to student learning and skills development? and (2) What are the difficulties when using this methodology? Three evaluation approaches were used: test scores, students' perceptions, and our observations of students' skills development during this project. It was observed that participating students demonstrated significant test score improvements, indicating enhanced learning, with reported challenges in effort and skill development, particularly in story creation and teamwork. Ultimately, this project allowed students to achieve several cognitive learning objectives, fostering the development of crucial skills like communication and problem-solving. The use of transmedia storytelling in undergraduate engineering courses has the potential to facilitate the cultivation of essential competencies for future engineers across a varied range of cognitive levels, albeit requiring considerable time for planning strategies and creating content.
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•The performance of four ML classification methods are compared for corrosion prediction.•Bagging classifier has the highest prediction accuracy (94.4%) for electrolyte-based ...datasets.•DT classifier has the best prediction accuracy (93.95%) for critical ions-based datasets.•Feature creation increased model generalizability.•The factors that contribute the most to corrosion are ranked using feature importance.
Corrosion behavior prediction of materials in any given environmental condition is important to minimize time-consuming experimental work to avoid failures and catastrophes in industry. Supervised machine learning (ML) techniques are recently explored to predict corrosion behavior. However, there is still a lack of research that proposes a model capable of predicting the corrosion behavior of a wide range of stainless steel grades in varying environments, including acids, bases, and salts. Moreover, conventional experimental approaches are often insufficient in identifying the most influential factors in the corrosion process due to its multivariate and non-linear nature.
This study presents the development and evaluation of multiple ML models in predicting the corrosion behavior of different types of stainless steel in varying environments. The prediction performance of four ML algorithms, decision tree (DT), support vector machine (SVM), random forest (RF), and bagging classifier, were compared. Initially, the algorithms were fitted to a dataset based on the type of electrolyte (Dataset No. 1) and then modeled on a modified dataset (Dataset No. 2) in which the types of electrolytes were replaced with their critical ions contributing to corrosion reactions. The Bagging classifier achieved the highest prediction accuracy of 94.4% for Dataset No. 1, while the DT model was the most suitable for Dataset No. 2 with a testing accuracy of 93.95%. The application-driven approach of confusion matrix analysis to select the model’s capacity to correctly identify severe and poor corrosion behavior confirmed that Bagging and DT classifiers are the most suitable ML algorithms for predicting corrosion behavior in Dataset No. 1 and No. 2, respectively. Furthermore, the feature importance analysis identified hydrogen and sulfide concentrations in corrosive environments, as well as the sum of the number of alloying elements, as the most influential factors, contributing up to 77.8% to the corrosion behavior. As a result, users of stainless steels can leverage this model to predict the corrosion behavior of specific materials in specific environments, facilitating informed material selection for various applications, without the need of lengthy and costly experiments.
The selection of the optimal material in engineering design procedures of any construction project due to the complexity of future circumstances could be considered as a complex problem. Similar ...complex selection problems can be efficiently implemented with the support of Multiple Attribute Decision Making (MADM) methods. The traditional MADM methods focus both on beneficial or non-beneficial attributes to determine a rank order of feasible alternatives and to select the best one. Nevertheless, like many engineering design problems, some attributes could be assessed based on target values. Therefore, target values of attributes along with beneficial and non-beneficial attributes makes a decision-making method more robust. Despite practical and functional applications of the target-based MADM approaches particularly in engineering design problems, only a few studies have made attempts to implement such methods. The presented study tackles a material selection problem by applying a hybrid decision-making approach supported on the Step-Wise Weight Assessment Ratio Analysis (SWARA) method and COmbinative Distance-based ASsessment (CODAS) technique containing target-based attributes. A case-study concerning the selection of optimal cement material type based on a real-world conceptual dam construction project in Iran has been analyzed by the proposed method considering two categories of attributes, i.e., managerial issues and technical specifications.
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